The invention pertains to methods of generating information about materials present in compositions, and in particular aspects pertains to methods of generating information about inclusions, impurities and/or other components present in metal compositions. The invention also pertains to methods of generating information about particulates present in fluids.
There are numerous applications in which it is desirable to obtain information about materials present in a composition. For instance, there are applications in which relatively high purity metal is desired, and in which it is accordingly also desired to obtain information about any impurities present in the metal composition. An exemplary application in which relatively high purity metals can be desired is the formation of sputtering targets. Targets can be formed of, for example, aluminum; aluminum+0.5% copper; copper; copper+from 1 to 100 ppm silver; and aluminum+0.5% copper+0.2% silicon. The targets are preferably xe2x80x9chigh purityxe2x80x9d, and accordingly are preferably at least 99.995% pure relative to the desired constituents therein. A second application in which high purity materials are desired is in the formation of solders, which can comprise, for example, one or more of lead, tin and silver.
A difficulty in forming targets, or any other high purity material, is that some level of impurity is generally within the material. The type and quantity of the impurity can determine if the impurity can be tolerated within the material, or if the impurity destroys the material for an intended purpose. For instance, it is common for impurities to be introduced during fabrication of sputtering targets from high purity metals. Such impurities can be introduced, for example, during the casting of the metals into a billet. Specifically, casting can use carbon or ceramic containers, such as crucibles and troughs. A small amount of material sometimes transfers from the containers into the metal. Impurities can also be introduced at processing steps other than casting. For instance, target materials can contact silicate or other oxides (such as, for example, aluminum oxide) during fabrication of sputtering targets, and accordingly various oxides can be introduced into the target material.
Impurity particles (such as, for example, carbon particles and/or oxide particles) can be problematic in sputtering target applications. For instance, a particle of impurity can result in an arc into target material proximate the particle. Such arc can cause displacement of relatively large particles of the material. The large particles can then deposit on a substrate wafer to cause so-called splattering on the substrate wafer. The splattering can be problematic in that it forms a less conformal and uniform coating on a substrate than does material which has not been splattered. As microelectronic devices become increasingly smaller, there is increasingly less tolerance for splattering.
The amount of splattering caused by impurities in a target material can be a function of the type of impurity, size of impurity, and quantity of the impurity. For instance, conductive impurities (like carbon) can, in some instances, be less problematic that insulative impurities (like oxides) in that the conductive impurities may be less likely to generate arcs. Further, large impurities can be more problematic than small impurities, in that large impurities can tend to cause more or larger splatters than small impurities. Finally, numerous impurities tend to be more problematic than less numerous impurities, in that numerous impurities will tend to cause more splattering events than would less numerous impurities.
Because the problems caused by inclusions and other impurities can vary depending on the type, size and quantity of impurities within a material, it is desirable to quantitate the impurities within a material by type, size and prevalence. Such quantification can be particularly useful during fabrication of sputtering targets if the quantification occurs after a metal is cast into a billet, and before the metal has been fabricated into a target. Specifically, if a problematic number, size and/or type of impurities are found in a cast material, the material can be identified as being inadequate for target fabrication before the time and expense of target fabrication have been invested into the material. Further, if type, quantity and/or size of impurities are identified within a cast material, such can provide clues as to the source of the impurities. Accordingly, such can enable improvement in a process of casting target materials to avoid introduction of impurities in future processes. Additionally, identification of quantity, size and/or type of impurities in materials can serve as a quality control test.
Another exemplary time when it can be particularly useful to quantitate target material impurities by size, prevalence and/or type is after the material has been formed and utilized as a target. Specifically, if the material is found to perform less than adequately as a target, it would be desirable to subject the material to analysis to determine if the problems associated with the target are caused by particular impurities within the target material.
For the above-described reasons, it would be desirable to develop methods for quantitating impurities in metal materials which could identify one or more of size, type and prevalence of the impurities. The above-described application of determining impurities relative to metal materials is but one of many applications wherein it is desired to identify specific components in particular materials. Accordingly, it would be further desirable to develop methods which were applicable to identifying components of not only metal materials, but also to materials other than metals.
In one aspect, the invention encompasses a method of generating information about materials (such as inclusions and other impurities, or such as desired components) present in a composition. A reagent is utilized to dissolve at least some of the composition (for purposes of interpreting this disclosure and the claims that follow, the term xe2x80x9creagentxe2x80x9d is to be understood to encompass one or both of a reactant and a solvent, unless it is specifically indicated otherwise). The dissolved composition is filtered through a substrate, and portions of the composition are retained on the substrate during the filtering. After the filtering, the substrate is scanned with a microscope. The scanning comprises automated displacement of the substrate relative to an observing portion of the microscope along a pattern (the pattern can be a grid, and can be any shape, including circular or rectangular). The microscope obtains data about the retained portions at locations along the pattern. Automated image processing generates information about one or more of the size, type and quantity of the retained portions of the composition.
In another aspect, the invention encompasses a method of generating information about impurities present in a metal composition. A reagent is utilized to selectively dissolve metallic portions of the composition relative to at least some impurities present in the metal composition. The dissolved metallic portions form a solution with the reagent. The impurities comprise at least two different types, with one of the at least two types being a first type and the another of the at least two types being a second type. The solution is filtered through a substrate. At least some of the first and second types of the impurities are retained on the substrate during the filtering. After the filtering, the substrate is scanned with a light microscope. The scanning comprises automated displacement of the substrate relative to an observing portion of the microscope along a grid pattern. The microscope obtains data about the impurities at locations along the grid pattern. The data includes a relative darkness (i.e., a contrast) of the impurities as compared to a background defined by the substrate. The first type of impurities are darker than the background, and the second type of impurities are lighter than the background. The data is processed to generate information about the size, quantity and type of the impurities.